Core protocol development for phase 2/3 clinical trials in the leukodystrophy Vanishing White Matter
Bibliographic record
Abstract
Abstract Background: The leukodystrophy “Vanishing White Matter” (VWM) is an orphan disease with neurological decline and high mortality. Currently, VWM has no approved treatments, but advances in understanding pathophysiology have led to identification of promising therapies. Several investigational medicinal products are either in or about to enter clinical trial phase. Clinical trials in VWM pose serious challenges, as VWM has an episodic disease course; disease phenotype is highly heterogeneous and predictable only for early onset; and study power is limited by the small patient numbers. To address these challenges and accelerate therapy delivery, the VWM Consortium, a group of academic clinicians with expertise in VWM, decided to develop a core protocol to function as a template for trials, to improve trial design and facilitate sharing of control data, while permitting flexibility regarding other trial details. Overall aims of the core protocol are to collect safety, tolerability, and efficacy data for treatment assessment and marketing authorization. Methods: To develop the core protocol, the VWM Consortium designated a committee, including clinician members of the VWM consortium, family and patient group advocates, and experts in statistics, clinical trial design and alliancing with industries. We drafted three age-specific protocols, to stratify into more homogeneous patient groups, of ages ≥18 years, ≥6 to <18 years and <6 years. We chose double‐blind, randomized, placebo-controlled design for patients aged ≥6 years; and open-label non-randomized natural-history-controlled design for patients <6 years. The protocol describes study populations, age-specific endpoints, inclusion and exclusion criteria, study schedules, sample size determinations, and statistical considerations. Discussion: The core protocol provides a shared uniformity across trials, enables a pool of shared controls, and reduces the total number of patients necessary per trial, limiting the number of patients on placebo. All VWM clinical trials are suggested to adhere to the core protocol. Other trial components such as choice of primary outcome, pharmacokinetics, pharmacodynamics, and biomarkers are flexible and unconstrained by the core protocol. Each sponsor is responsible for their trial execution, while the control data are handled by a shared research organization. This core protocol benefits the efficiency of parallel and consecutive trials in VWM, and we hope accelerates time to availability of treatments for VWM. Trial registration : NA
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".